It decides the number on the quote. You just sign it.
Somewhere right now, a B2B sales rep is staring at a quote for a custom industrial order - a few hundred line items, a customer who always pushes, a number due in an hour. Instinct says: discount it, close it, move on. That instinct, multiplied across thousands of deals a year, is exactly how a healthy company bleeds profit one reasonable-sounding concession at a time. The leak is invisible. It has no alarm. It just shows up, eventually, as a margin that mysteriously refuses to grow.
Vendavo is the software sitting between that rep and the regret. Quietly, in the half-second before the quote goes out, it has already done the math the human can't: what this customer has paid before, what similar customers pay, where the floor really is, and what number actually closes without surrendering profit. It is not glamorous work. It is enormously valuable work. And Vendavo has been doing it since 1998.
Ask a hundred manufacturers how they set prices and ninety will describe some combination of last year's list, a gut feel for the market, and whatever the customer's procurement team manages to argue them down to. It works, roughly, the way a thermostat set by licking your finger and holding it up works. Vendavo's entire thesis is that there is a better number hiding in the data, and that finding it - deal by deal, product by product, region by region - is worth real money.
The company calls its ambition an AI-native Commercial Operating System: one platform where pricing, quoting and rebates stop being three disconnected spreadsheets and start being a single, governed system. The catch with AI in pricing is trust - no sales leader signs off on a number they can't explain to the customer. So Vendavo leans on explainable AI: recommendations that come with their reasoning attached. The algorithm doesn't just say "charge $4.12." It says why.
Vendavo's products map neatly to the life of a deal: figure out the right price, get the quote out fast, then measure what actually happened to the margin.
AI-driven guidance for negotiated pricing - recommends the optimal price and the approval threshold for each individual deal.
Configure-price-quote software that speeds quotes, enforces governance, and clears the approval logjam.
Shows exactly how and why margins moved - across price, volume, mix and cost.
Price and profit diagnostics that surface leakage and opportunity across the price waterfall.
Automates rebate programs, accruals and channel incentives so payouts stop becoming guesswork.
Cross-sell and upsell recommendations that quietly grow the size of the deal.
Global price-list management plus optimization, powered by pricing science and AI.
Vendavo's home turf is the gap between the list price and what a deal actually nets after every discount, rebate and concession. Each step down is small. The cumulative drop is not. Below: an illustrative waterfall - approximate figures to show the shape of the problem Vendavo attacks.
FIG. 2 - Illustrative only. The point isn't the exact numbers; it's that the last column is the one that pays the bills, and most companies can't see it clearly.
Vendavo's customers are the kind of industrial heavyweights whose catalogs run to hundreds of thousands of SKUs - exactly the businesses where a single point of margin is a serious sum. Publicly referenced names include:
Customers report the kind of results that make a CFO sit up: 90% of quotes going out within four hours and 75% requiring no pricing approval at all - the bottleneck, dissolved.
Back to our rep with the hour-long deadline and the itchy discount finger. With Vendavo in the workflow, the quote is already built - hundreds of line items configured, priced and approved before lunch. The recommended number sits on the screen with its reasoning attached, so the rep can defend it to procurement instead of caving to it. The deal closes. The margin holds. Nobody throws a parade.
And that is precisely the point. Vendavo's whole job is to make the invisible leak visible, then close it - not with a dramatic intervention, but with a better number, delivered on time, deal after deal. The company that started in 1998 chasing the right price has turned a quarter-century of patience into something genuinely useful: a way for the world's manufacturers to stop guessing, and start knowing, what their work is actually worth.